Deep mutational scanning reveals the molecular determinants of RNA polymerase-mediated adaptation and tradeoffs

RNA polymerase (RNAP) is emblematic of complex biological systems that control multiple traits involving trade-offs such as growth versus maintenance. Laboratory evolution has revealed that mutations in RNAP subunits, including RpoB, are frequently selected. However, we lack a systems view of how mutations alter the RNAP molecular functions to promote adaptation. We, therefore, measured the fitness of thousands of mutations within a region of rpoB under multiple conditions and genetic backgrounds, to find that adaptive mutations cluster in two modules. Mutations in one module favor growth over maintenance through a partial loss of an interaction associated with faster elongation. Mutations in the other favor maintenance over growth through a destabilized RNAP-DNA complex. The two molecular handles capture the versatile RNAP-mediated adaptations. Combining both interaction losses simultaneously improved maintenance and growth, challenging the idea that growth-maintenance tradeoff resorts only from limited resources, and revealing how compensatory evolution operates within RNAP.

Table 3).Finally, we also reconstructed and individually measured growth for multiple mutations.More information can be found subsequently in the text.
Mutations to residues with similar properties, such as leucine-isoleucine, may have fitness comparable to wild-type.Therefore, if certain positions had only such similar substitutions, their mean growth-associated fitness and mean stringent enrichment would be underestimated due to undersampling.To verify the diversity of substitutions, we used the Grantham score, which is a measure of amino acid distance based on: composition, polarity, and molecular volume 1 .We mapped the residuewise distribution of the Grantham score for all substitutions.We scored 5 +/-1 and 8 +/-2 nonsynonymous substitutions per position for growth and stringent enrichment respectively.We observed that substitutions at each position covered a broad distribution of Grantham scores at all positions.
Additionally, the distribution of the Grantham score was comparable between stringent versus nonstringent and growth-promoting versus non-growth-promoting residues (Supplementary Figure S1E   and S1F).

Supplementary Note 2: Epistasis and means to determine interactions
Epistasis occurs when the actual fitness of a double mutant deviates from (is greater than or lower than) the sum of fitness of individual mutations.If we have mutations A, B and their combination AB, and fitness associated with each mutation is fA, fB and fAB then epistasis is measured as: ɛAB = fAB -(fA+ fB) if ɛAB > 0, then the epistasis is positive and when ɛAB < 0, then the epistasis is negative.Epistasis between two residues usually suggests interactions.However, in the case of negative epistasis, a negative impact of combining two mutations on the function could be also due altered protein stability because two mutations are more likely to affect protein stability as compared to one.However, Positive epistasis i.e., cases where the actual fitness in greater than the sum of fitness is a more conclusive result of functional interactions.In the figures, 4 and 5, we only demonstrate significant positive epistasis.
We determined the significance of the epistatic interaction by using the combination of synonymous mutations as a control.Usually, a combination of synonymous mutations should not have any functional hypothesis.As expected the distribution of ɛAB for combination of synonymous mutations centered around 0 (Figure S4).Therefore, a distribution of ɛAB for synonymous mutations gives us the range for a null hypothesis: an absence of epistasis.Only ɛAB values greater than mean (ɛAB for combination of synonymous mutations) + 1.96 * (standard deviation of ɛAB for combination of synonymous mutations) to obtain a p < 0.05, we considered as significant (Figure S4 for the range).

Supplementary Fig. 1: Mutation library statics and evolution experiment:
a. Frequency of non-synonymous and synonymous mutations within the library.A variant is considered non-synonymous if at least one of the mutations in the variant is non-synonymous.
A variant is considered synonymous if all mutations are synonymous.b.Histogram of number of mutations per variants.c.Growth rate of Escherichia coli MG1655 strain in the multiple evolution environments from left to right: M9 minimal media with Glucose, M9 minimal media with Glycerol, M9 minimal media with Galactose, M9 minimal media with Glucose and 0.3M NaCl, M9 minimal media with Glucose and 0.6% (v/v) butanol.Bars represent mean +/-SD associated with n = 3 replicates.d.In each environment, the evolution was performed for 30 generations.Bottles with each media were inoculated to an initial OD of 0.005.When the optical density reached and OD (600 nm) of 0.18-0.2, the cells were inoculated in a new bottle with fresh media at a 1:32 dilution.In the figure, each blue line represents the tracking of the optical density in each cycle.The evolution was performed in two biological replicates A (solid line) and B (dashed line).e.A position-wise distribution of Grantham score for all (gray) and beneficial mutations (red) for substitutions scored in the stringent selection.(The Grantham score measures the distance of a protein substitution based on chemical properties based on composition, polarity and molecular volume.f.A position-wise distribution of Grantham score for all (gray) and beneficial mutations (red) for substitutions scored in the growth selection.(The Grantham score measures the distance of a protein substitution based on chemical properties based on composition, polarity and molecular volume.